Toward clinically usable CAD for lung cancer screening with computed tomography

Objectives

The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice.

Methods

A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set.

Results

The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules?≥?4 mm and 100 (±8.33) for nodules?≥?8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90.

Conclusions

The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality.

Key Points

? CAD requirements can be based on lung cancer screening trial results. ? CAD systems can be evaluated using publically available annotated CT image databases. ? A new CAD system was developed with a low false positive rate. ? The CAD system has reliable measurement tools needed for clinical use.     

Long-term follow-up of non-calcified pulmonary nodules (<10?mm) identified during low-dose CT screening for lung cancer

Objectives

To assess the long-term stability of small (<10?mm) non-calcified pulmonary nodules (NCNs) in high-risk subjects initially screened for lung cancer using low-dose chest computed tomography (LDCCT).

Methods

A total of 449 subjects initially underwent screening with serial LDCCT over a 2-year period. Participants identified as having NCNs ≥10?mm were referred for formal lung cancer workup. NCNs <10?mm diameter were followed in accordance with the study protocol. Seven?years after baseline screening, subjects with previously documented NCNs <10?mm, which were unchanged in size after the 2-year follow-up period, were re-imaged using LDCCT to assess for interval nodule growth.

Results

Eighty-three subjects with previously documented stable NCNs <10?mm underwent LDCCT at 7?years. NCNs were unchanged in 78 subjects and had decreased in size in 4 subjects. There was interval growth of an NCN (from 6?mm to 9?mm) in one subject re-imaged at 7?years, but this nodule has remained stable in size over a further 2-year follow-up period.

Conclusions

Non-calcified pulmonary nodules <10?mm in size that are unchanged in size or smaller after 2?years of follow-up with LDCCT are most likely benign.

Key Points

? Computed tomography is increasingly used for screening for lung cancer. ? However CT frequently reveals unsuspected lung nodules. ? Seven-year follow-up of small (<10?mm) non-calcified pulmonary nodules is reassuring. ? Even in high-risk patients most nodules will likely be benign.     

Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals

Objective

To retrospectively investigate whether optimisation of volume-doubling time (VDT) cutoff for fast-growing nodules in lung cancer screening can reduce false-positive referrals.

Methods

Screening participants of the NELSON study underwent low-dose CT. For indeterminate nodules (volume 50–500 mm³), follow-up CT was performed 3 months after baseline. A negative baseline screen resulted in a regular second-round examination 1 year later. Subjects referred to a pulmonologist because of a fast-growing (VDT <400 days) solid nodule in the baseline or regular second round were included in this study. Histology was the reference for diagnosis, or stability on subsequent CTs, confirming benignity. Mean follow-up of non-resected nodules was 4.4 years. Optimisation of the false-positive rate was evaluated at maintained sensitivity for lung cancer diagnosis with VDT <400 days as reference.

Results

Sixty-eight fast-growing nodules were included; 40 % were malignant. The optimal VDT cutoff for the 3-month follow-up CT after baseline was 232 days. This cutoff reduced false-positive referrals by 33 % (20 versus 30). For the regular second round, VDTs varied more among malignant nodules, precluding lowering of the VDT cutoff of 400 days.

Conclusion

All malignant fast-growing lung nodules referred after the 3-month follow-up CT in the baseline lung cancer screening round had VDT ≤232 days. Lowering the VDT cutoff may reduce false-positive referrals.

Key Points

? Lung nodules are common in CT lung cancer screening, most being benign ? Short-term follow-up CT can identify fast-growing intermediate-size lung nodules ? Most fast-growing nodules on short-term follow-up CT still prove to be benign ? A new volume-doubling time (VDT) cut-off is proposed for lung screening ? The optimised VDT cutoff may decrease false-positive case referrals for lung cancer     

Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database

Objectives

To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show that CAD finds lesions not identified by the LIDC’s four-fold double reading process.

Methods

The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system.

Results

The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study.

Conclusions

On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process.

Key Points

? CAD systems should be validated on public, heterogeneous databases. ? The LIDC/IDRI database is an excellent database for benchmarking nodule CAD. ? CAD can identify the majority of pulmonary nodules at a low false positive rate. ? CAD can identify nodules missed by an extensive two-stage annotation process.

     

Evaluation of a method of computer-aided detection (CAD) of pulmonary nodules at computed tomography

Purpose

The authors sought to compare the sensitivity and reading time obtained using computer-aided detection (CAD) software as second reader (SR) or concurrent reader (CR) in the identification of pulmonary nodules.

Materials and methods

Unenhanced CT scans of 100 consecutive cancer patients were retrospectively reviewed by four readers to identify all solid, noncalcified pulmonary nodules ranging from 3 to 30 mm in diameter. The sensitivity and reading time of each reader and of CAD alone were calculated at 3-mm and 5-mm thresholds with respect to the reference standard, consisting of a consensus reading by the four radiologists involved in the study. The McNemar test was used to compare the sensitivities obtained by reading without CAD (readers 1 and 2), with CAD as SR (readers 1 and 2 with a 2-month delay), and with CAD as CR (readers 3 and 4). The paired Student’s t test was used to compare reading times. A value of p<0.05 was considered statistically significant.

Results

A total of 258 and 224 nodules were identified at 3-mm and 5-mm thresholds, respectively. The sensitivity of CAD alone was 62.79% and 67.41% at the 3-mm and 5-mm threshold values respectively, with 4.15 and 2.96 false-positive findings per examination. CAD as SR produced a significant increase in sensitivity (p<0.001) in nodule detection with respect to reading without CAD both at 3 mm (12.01%) and 5 mm (10.04%); the average increase in sensitivity obtained when comparing CAD as SR to CAD as CR was statistically significant (p<0.025) both at the 3-mm (5.35%) and 5-mm (4.68%) thresholds. CAD as CR produced a nonsignificant increase in sensitivity compared with reading without CAD (p>0.05). Mean reading time using CAD as SR (330 s) was significantly longer than reading without CAD (135 s, p<0.001) and reading with CAD as CR (195 s, p<0.025).

Conclusions

The use of CAD as CR, without any significant increase in reading time, produces no significant increase in sensitivity in pulmonary nodule detection when compared with reading without CAD (p>0.05); CAD as SR, at the cost of longer reading times, increases sensitivity when compared with reading without CAD (p<0.001) or with CAD as CR (p<0.025).     

Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

Purpose

To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA).

Materials and Methods

We included CTPA examinations of 79 patients (50 female, 52?±?18?years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3?months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used ??² and McNemar testing.

Results

Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers?? initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p?p?=?0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p?=?0.125).

Conclusion

Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives.     

Comparison of chest radiography,chest digital tomosynthesis and low dose MDCT to detect small ground-glass opacity nodules: an anthropomorphic chest phantom study

Objectives

The purpose of this study was to evaluate the diagnostic performance of chest radiography (CXR), chest digital tomosynthesis (DT) and low dose multidetector computed tomography (LDCT) for the detection of small pulmonary ground-glass opacity (GGO) nodules, using an anthropomorphic chest phantom.

Methods

Artificial pulmonary nodules were placed in a phantom and a total of 40 samples of different nodule settings underwent CXR, DT and LDCT. The images were randomly read by three experienced chest radiologists. Free-response receiver-operating characteristics (FROC) were used.

Results

The figures of merit for the FROC curves averaged for the three observers were 0.41, 0.37 and 0.76 for CXR, DT and LDCT, respectively. FROC analyses revealed significantly better performance of LDCT over CXR or DT for the detection of GGO nodules (P?P?=?0.73).

Conclusion

The diagnostic performance of DT for the detection of pulmonary small GGO nodules was not significantly different from that of CXR, but LDCT performed significantly better than both CXR and DT. DT is not a suitable alternative to CT for small GGO nodule detection, and LDCT remains the method of choice for this purpose.

Key Points

? For GGO nodule detection, DT was not significantly different from CXR. ? DT is not a suitable alternative to CT for GGO nodule detection. ? LDCT is the method of choice for GGO nodule detection.     

Sensitivity and accuracy of volumetry of pulmonary nodules on low-dose 16- and 64-row multi-detector CT: an anthropomorphic phantom study

Objective

To assess the sensitivity of detection and accuracy of volumetry by manual and semi-automated quantification of artificial pulmonary nodules in an anthropomorphic thoracic phantom on low-dose CT.

Methods

Fifteen artificial spherical nodules (diameter 3, 5, 8, 10 and 12?mm; CT densities -800, -630 and +100 HU) were randomly placed inside an anthropomorphic thoracic phantom. The phantom was examined on 16- and 64-row multidetector CT with a low-dose protocol. Two independent blinded observers screened for pulmonary nodules. Nodule diameter was measured manually, and volume calculated. For solid nodules (+100 HU), diameter and volume were also evaluated by semi-automated software. Differences in observed volumes between the manual and semi-automated method were evaluated by a t-test.

Results

Sensitivity was 100?% for all nodules of >5?mm and larger, 60?C80?% for solid and 0?C20?% for non-solid 3-mm nodules. No false-positive nodules but high inter-observer reliability and inter-technique correlation were found. Volume was underestimated manually by 24.1?±?14.0?% for nodules of any density, and 26.4?±?15.5?% for solid nodules, compared with 7.6?±?8.5?% (P?<?0.01) semi-automatically.

Conclusion

In an anthropomorphic phantom study, the sensitivity of detection is 100?% for nodules of >5?mm in diameter. Semi-automated volumetry yielded more accurate nodule volumes than manual measurements.

Key Points

? Computed tomography has become the definitive investigation of the chest. ? Low-dose CT techniques have recently been introduced. ? Low-dose CT is reliable for detecting spherical pulmonary nodules of >5?mm. ? Semi-automated volumetry is more accurate than manual measurement for pulmonary nodules. ? No difference in the accuracy of volumetry was found between 16- and 64- MDCT.     

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably

Objective

We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms.

Methods

In a lung cancer screening trial, 188 baseline nodules >5 mm were identified. Including follow-ups, these nodules formed a study-set of 545 nodules. Nodules were independently double read by two readers using commercially available volumetry software. The software offers readers three different analysing algorithms. We compared the inter-observer variability of nodule volumetry when the readers used the same and different algorithms.

Results

Both readers were able to correctly segment and measure 72% of nodules. In 80% of these cases, the readers chose the same algorithm. When readers used the same algorithm, exactly the same volume was measured in 50% of readings and a difference of >25% was observed in 4%. When the readers used different algorithms, 83% of measurements showed a difference of >25%.

Conclusion

Modern volumetric software failed to correctly segment a high number of screen detected nodules. While choosing a different algorithm can yield better segmentation of a lung nodule, reproducibility of volumetric measurements deteriorates substantially when different algorithms were used. It is crucial even in the same software package to choose identical parameters for follow-up.     

Optimal image reconstruction for detection and characterization of small pulmonary nodules during low-dose CT

Objectives

To optimize the slice thickness/overlap parameters for image reconstruction and to study the effect of iterative reconstruction (IR) on detectability and characterization of small non-calcified pulmonary nodules during low-dose thoracic CT.

Materials and methods

Data was obtained from computer simulations, phantom, and patient CTs. Simulations and phantom CTs were performed with 9 nodules (5, 8, and 10 mm with 100, ?630, and ?800 HU). Patient data were based on 11 ground glass opacities (GGO) and 9 solid nodules. For each analysis the nodules were reconstructed with filtered back projection and IR algorithms using 10 different combinations of slice thickness/overlap (0.5–5 mm). The attenuation (CT#) and the contrast to noise ratio (CNR) were measured. Spearman’s coefficient was used to correlate the error in CT# measurements and slice thickness. Paired Student’s t test was used to measure the significance of the errors.

Results

CNR measurements: CNR increases with increasing slice thickness/overlap for large nodules and peaks at 4.0/2.0 mm for smaller ones. Use of IR increases the CNR of GGOs by 60 %. CT# measurements: Increasing slice thickness/overlap above 3.0/1.5 mm results in decreased CT# measurement accuracy.

Conclusion

Optimal detection of small pulmonary nodules requires slice thickness/overlap of 4.0/2.0 mm. Slice thickness/overlap of 2.0/2.0 mm is required for optimal nodule characterization. IR improves conspicuity of small ground glass nodules through a significant increase in nodule CNR.

Key Points

? Slice thickness/overlap affects the accuracy of pulmonary nodule detection and characterization. ? Slice thickness ≥3 mm increases the risk of misclassifying small nodules. ? Optimal nodule detection during low-dose CT requires 4.0/2.0-mm reconstructions. ? Optimal nodule characterization during low-dose CT requires 2.0/2.0-mm reconstructions. ? Iterative reconstruction improves the CNR of ground glass nodules by 60 %.     

Persistent pulmonary subsolid nodules: model-based iterative reconstruction for nodule classification and measurement variability on low-dose CT

Objectives

To compare the pulmonary subsolid nodule (SSN) classification agreement and measurement variability between filtered back projection (FBP) and model-based iterative reconstruction (MBIR).

Methods

Low-dose CTs were reconstructed using FBP and MBIR for 47 patients with 47 SSNs. Two readers independently classified SSNs into pure or part-solid ground-glass nodules, and measured the size of the whole nodule and solid portion twice on both reconstruction algorithms. Nodule classification agreement was analyzed using Cohen’s kappa and compared between reconstruction algorithms using McNemar’s test. Measurement variability was investigated using Bland–Altman analysis and compared with the paired t-test.

Results

Cohen’s kappa for inter-reader SSN classification agreement was 0.541–0.662 on FBP and 0.778–0.866 on MBIR. Between the two readers, nodule classification was consistent in 79.8 % (75/94) with FBP and 91.5 % (86/94) with MBIR (p?=?0.027). Inter-reader measurement variability range was -5.0–2.1 mm on FBP and -3.3–1.8 mm on MBIR for whole nodule size, and was -6.5–0.9 mm on FBP and -5.5–1.5 mm on MBIR for solid portion size. Inter-reader measurement differences were significantly smaller on MBIR (p?=?0.027, whole nodule; p?=?0.011, solid portion).

Conclusions

MBIR significantly improved SSN classification agreement and reduced measurement variability of both whole nodules and solid portions between readers.

Key Points

? Low-dose CT using MBIR algorithm improves reproducibility in the classification of SSNs. ? MBIR would enable more confident clinical planning according to the SSN type. ? Reduced measurement variability on MBIR allows earlier detection of potentially malignant nodules.     

Pulmonary nodules and masses in lung transplant recipients: clinical and CT findings

Objectives

The purpose of this study was to review the clinical and CT findings of pulmonary nodules and masses in lung transplant recipients and to determine distinguishing features among the various aetiologies.

Methods

This retrospective study included 106 lung transplant recipients who had a chest CT performed over a 7-year period in a single institution.

Results

Twenty-four cases of pulmonary nodules and masses were observed on CT. Among the single lesions, three (50 %) were due to infections, one (17 %) to organizing pneumonia, and two (33 %) remained of undetermined origin. Among the multiple lesions, 14 (78 %) were due to infection, three to post-transplant lymphoproliferative disorder (17 %), and one to bronchogenic carcinoma (5 %). The two main microorganisms were P. aeruginosa and Aspergillus spp. Among 12 solid nodules >?1 cm, four (33 %) were due to malignancy: three post-transplant lymphoproliferative disorders (25 %), and one bronchogenic carcinoma (8 %). Among five cavitary nodules four (80 %) were due to aspergillosis.

Conclusion

Infection is the most frequent aetiology of pulmonary nodules and masses in lung transplant recipients, but other causes such as post-transplant lymphoproliferative disorder, bronchogenic carcinoma, or organizing pneumonia should be considered.

Key points

? Pulmonary nodules and masses are frequent in lung transplant recipients. ? Infection is the most frequent aetiology of solitary and multiple pulmonary nodules. ? Differential diagnosis includes post-transplant lymphoproliferative disorder, bronchogenic carcinoma, and organizing pneumonia. ? Clinical and CT findings are often non-specific. ? CT findings may be suggestive of some aetiologies that justify a biopsy.     

Standalone computer-aided detection compared to radiologists�� performance for the detection of mammographic masses

Objectives

We developed a computer-aided detection (CAD) system aimed at decision support for detection of malignant masses and architectural distortions in mammograms. The effect of this system on radiologists' performance depends strongly on its standalone performance. The purpose of this study was to compare the standalone performance of this CAD system to that of radiologists.

Methods

In a retrospective study, nine certified screening radiologists and three residents read 200 digital screening mammograms without the use of CAD. Performances of the individual readers and of CAD were computed as the true-positive fraction (TPF) at a false-positive fraction of 0.05 and 0.2. Differences were analysed using an independent one-sample t-test.

Results

At a false-positive fraction of 0.05, the performance of CAD (TPF?=?0.487) was similar to that of the certified screening radiologists (TPF?=?0.518, P?=?0.17). At a false-positive fraction of 0.2, CAD performance (TPF?=?0.620) was significantly lower than the radiologist performance (TPF?=?0.736, P <0.001). Compared to the residents, CAD performance was similar for all false-positive fractions.

Conclusions

The sensitivity of CAD at a high specificity was comparable to that of human readers. These results show potential for CAD to be used as an independent reader in breast cancer screening.

Key points

? Computer-aided detection (CAD) systems are used to detect malignant masses in mammograms ? Current CAD systems operate at low specificity to avoid perceptual oversight ? A CAD system has been developed that operates at high specificity ? The performance of the CAD system is approaching that of trained radiologists ? CAD has the potential to be an independent reader in screening     

Significance of pulmonary nodules in patients with colorectal cancer

Objectives

Radiographically small pulmonary nodules (PNs) in patients with colorectal cancer are troublesome because their discovery raises concern about metastases. This study sought to establish the appropriate timing of radiological follow-up for PNs detected at initial staging evaluation of colorectal carcinoma patients.

Methods

The medical records of 376 consecutive colorectal cancer patients who underwent curative surgery and had baseline and follow-up chest X-rays (CXR) and computed tomography (CT) were reviewed.

Results

The study included 92 patients who had all CXR and chest CT available for review, at least one PN found on baseline imaging, and no synchronous neoplasms. On baseline chest CT, these 92 patients had 170 PNs altogether and 77 (45.2?%) of them were greater than 5?mm in size. Baseline CXR detected 13 PNs in 12 patients and all but 2 were larger than 5?mm. Nodule size greater than 5?mm and irregular margins were predictors of nodule growth. The mean doubling time of 24/170 (14.1?%) growing PNs was about 4?months.

Conclusions

Our findings suggest that baseline and follow-up CXR are pointless, and short-interval CT follow-up is warranted when PNs larger than 5?mm with irregular margins are detected on preoperative chest CT.

Key Points

? Pulmonary nodules in colorectal cancer patients raise concern about metastasis. ? Baseline and follow-up chest X-ray in colorectal cancer can be abandoned. ? CT is the best technique for assessing PNs in colorectal cancer. ? Short-interval CT follow-up advisable for PNs larger than 5?mm with irregular margins.     

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study

Objective:

The purpose of this study was to assess accuracy of lung nodule volumetry in low-dose CT with application of iterative reconstruction (IR) according to nodule size, nodule density and CT tube currents, using artificial lung nodules within an anthropomorphic thoracic phantom.

Methods:

Eight artificial nodules (four diameters: 5, 8, 10 and 12 mm; two CT densities: −630 HU that represents ground-glass nodule and +100 HU that represents solid nodule) were randomly placed inside a thoracic phantom. Scans were performed with tube current–time product to 10, 20, 30 and 50 mAs. Images were reconstructed with IR and filtered back projection (FBP). We compared volume estimates to a reference standard and calculated the absolute percentage error (APE).

Results:

The APE of all nodules was significantly lower when IR was used than with FBP (7.5 ± 4.7% compared with 9.0 ±6.9%; p < 0.001). The effect of IR was more pronounced for smaller nodules (p < 0.001). IR showed a significantly lower APE than FBP in ground-glass nodules (p < 0.0001), and the difference was more pronounced at the lowest tube current (11.8 ± 5.9% compared with 21.3 ± 6.1%; p < 0.0001). The effect of IR was most pronounced for ground-glass nodules in the lowest CT tube current.

Conclusion:

Lung nodule volumetry in low-dose CT by application of IR showed reliable accuracy in a phantom study. Lung nodule volumetry can be reliably applicable to all lung nodules including small, ground-glass nodules even in ultra-low-dose CT with application of IR.

Advances in knowledge:

IR significantly improved the accuracy of lung nodule volumetry compared with FBP particularly for ground-glass (−630 HU) nodules. Volumetry in low-dose CT can be utilized in patient with lung nodule work-up, and IR has benefit for small, ground-glass lung nodules in low-dose CT.The volumetric measurement of a lung nodule with CT imaging is more accurate and consistent in the detection of growth and determination of tumour doubling time than simple manual axial diameter measurements used in the New Response Evaluation Criteria in Solid Tumours (revised RECIST guideline v. 1.1).^1,2 The recent Dutch–Belgian randomized lung cancer screening trial (NELSON) nodule management protocol was based on volumetric nodule assessment. A test was considered to be positive if the solid component of a nodule measured >500 mm³, or if the solid component of a nodule was 50–500 mm³ when the volume doubling time was less than 400 days.³ Therefore, pulmonary nodule volumetry is used for nodule identification and diagnostic strategy guidance in the follow-up of lung cancer screening as well as for monitoring tumour response to therapy.The increase in the use of CT has raised concern about the increasing risk of cancer from medical radiation exposure.⁴ Thoracic CT has been widely used in variable disease entities and frequent follow-up CT examinations may be needed. Additionally, lung cancer screening using CT is becoming more common. Therefore, further reduction of the radiation exposure during chest CT examinations would be required, and radiation dose reduction is very important issue in lung cancer screening and in lung nodule work-up. For lowering the radiation dose, the use of iterative reconstruction (IR) algorithms has become available, due to advances in technology and increased computational power. IR provides imaging at lower radiation doses with similar noise levels compared with routine-dose conventional filtered back projection (FBP), allowing dose reduction without compromising on image quality and diagnostic value.^5–10 Among the several IR algorithms offered by different vendors, we used adaptive iterative dose reduction system using a three-dimensional processing algorithm (AIDR 3D; Toshiba Medical Systems, Otawara, Japan).The accuracy of volumetric measurements of lung nodules can be affected by many sources of variability, such as nodule characteristics, CT scan parameters and measurement technology.^11–15 Several studies have examined the accuracy of volumetric measurement of lung nodules in low-dose CT.^16–18 However, it is still not well known whether IR algorithm can be a source of variability in nodule volume measurement. Furthermore, the effect of lower dose CT on volumetric measurement in relation to nodule density and image reconstruction algorithm has not been investigated.The purpose of this study was to assess the accuracy of lung nodule volumetry in low-dose CT using IR according to different nodule sizes, nodule densities, CT tube currents and scan types using spherical synthetic pulmonary nodules inside an anthropomorphic thoracic phantom.     

Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance

Objective

The diagnostic performance of radiologists using incremental CAD assistance for lung nodule detection on CT and their temporal variation in performance during CAD evaluation was assessed.

Methods

CAD was applied to 20 chest multidetector-row computed tomography (MDCT) scans containing 190 non-calcified ≥3-mm nodules. After free search, three radiologists independently evaluated a maximum of up to 50 CAD detections/patient. Multiple free-response ROC curves were generated for free search and successive CAD evaluation, by incrementally adding CAD detections one at a time to the radiologists’ performance.

Results

The sensitivity for free search was 53% (range, 44%–59%) at 1.15 false positives (FP)/patient and increased with CAD to 69% (range, 59–82%) at 1.45 FP/patient. CAD evaluation initially resulted in a sharp rise in sensitivity of 14% with a minimal increase in FP over a time period of 100 s, followed by flattening of the sensitivity increase to only 2%. This transition resulted from a greater prevalence of true positive (TP) versus FP detections at early CAD evaluation and not by a temporal change in readers’ performance. The time spent for TP (9.5 s?±?4.5 s) and false negative (FN) (8.4 s?±?6.7 s) detections was similar; FP decisions took two- to three-times longer (14.4 s?±?8.7 s) than true negative (TN) decisions (4.7 s?±?1.3 s).

Conclusions

When CAD output is ordered by CAD score, an initial period of rapid performance improvement slows significantly over time because of non-uniformity in the distribution of TP CAD output and not to a changing reader performance over time.     

Cardiac valve calcifications on low-dose unenhanced ungated chest computed tomography: inter-observer and inter-examination reliability,agreement and variability

Objectives

To determine inter-observer and inter-examination variability for aortic valve calcification (AVC) and mitral valve and annulus calcification (MC) in low-dose unenhanced ungated lung cancer screening chest computed tomography (CT).

Methods

We included 578 lung cancer screening trial participants who were examined by CT twice within 3 months to follow indeterminate pulmonary nodules. On these CTs, AVC and MC were measured in cubic millimetres. One hundred CTs were examined by five observers to determine the inter-observer variability. Reliability was assessed by kappa statistics (κ) and intra-class correlation coefficients (ICCs). Variability was expressed as the mean difference ± standard deviation (SD).

Results

Inter-examination reliability was excellent for AVC (κ?=?0.94, ICC?=?0.96) and MC (κ?=?0.95, ICC?=?0.90). Inter-examination variability was 12.7?±?118.2 mm³ for AVC and 31.5?±?219.2 mm³ for MC. Inter-observer reliability ranged from κ?=?0.68 to κ?=?0.92 for AVC and from κ?=?0.20 to κ?=?0.66 for MC. Inter-observer ICC was 0.94 for AVC and ranged from 0.56 to 0.97 for MC. Inter-observer variability ranged from -30.5?±?252.0 mm³ to 84.0?±?240.5 mm³ for AVC and from -95.2?±?210.0 mm³ to 303.7?±?501.6 mm³ for MC.

Conclusions

AVC can be quantified with excellent reliability on ungated unenhanced low-dose chest CT, but manual detection of MC can be subject to substantial inter-observer variability. Lung cancer screening CT may be used for detection and quantification of cardiac valve calcifications.

Key points

? Low-dose unenhanced ungated chest computed tomography can detect cardiac valve calcifications. ? However, calcified cardiac valves are not reported by most radiologists. ? Inter-observer and inter-examination variability of aortic valve calcifications is sufficient for longitudinal studies. ? Volumetric measurement variability of mitral valve and annulus calcifications is substantial.     

Assessment of pulmonary melanoma metastases with 18F-FDG PET/CT: which PET-negative patients require additional tests for definitive staging?

Objectives

To determine, in patients with melanoma, the dependence of PET sensitivity on pulmonary metastasis size, and to determine patients who require further evaluation for definite staging.

Methods

Of 183 melanoma patients who underwent ¹⁸F-fluorodeoxyglucose PET/computed tomography (CT) for staging or follow-up between January 2008 and June 2011, 38 patients (18 women and 20 men; mean age 62.0?±?14.7?years) with one or more pulmonary metastases visible on CT were included in the retrospective study. Each pulmonary metastasis was rated as positive or negative on PET, and lesion size (maximum transverse diameter) was assessed on CT. PET sensitivity was calculated according to the lesions’ size, in 2-mm steps.

Results

A total of 181 pulmonary metastases were analysed. PET sensitivity was 7.9?% for lesions of 4–5?mm; 33.3?% for lesions of 6–7?mm; 56.8?% for lesions of 8–9?mm; 63.6?% for lesions of 10–11?mm; 100?% for lesions of 12–14?mm; and 100?% for lesions of at least 15?mm. The differences in sensitivity between the size groups were significant (P?<?0.001)

Conclusions

With current state-of-the-art PET/CT technology, additional tests are necessary for definitive staging of melanoma patients who have one or more PET-negative lung nodules less than 12?mm in diameter on expiratory CT.

Key Points

? PET cannot rule out malignancy in pulmonary nodules less than 12?mm on expiratory CT. ? Melanoma patients with PET-negative pulmonary nodules less than 12?mm require additional tests. ? Knowledge of these factors can help interpretation of PET and PET/CT findings.     

Lung cancer perfusion: can we measure pulmonary and bronchial circulation simultaneously?

Objective

To describe a new CT perfusion technique for assessing the dual blood supply in lung cancer and present the initial results.

Methods

This study was approved by the institutional review board. A CT protocol was developed, and a dual-input CT perfusion (DI-CTP) analysis model was applied and evaluated regarding the blood flow fractions in lung tumours. The pulmonary trunk and the descending aorta were selected as the input arteries for the pulmonary circulation and the bronchial circulation respectively. Pulmonary flow (PF), bronchial flow (BF), and a perfusion index (PI, = PF/ (PF + BF)) were calculated using the maximum slope method. After written informed consent was obtained, 13 consecutive subjects with primary lung cancer underwent DI-CTP.

Results

Perfusion results are as follows: PF, 13.45?±?10.97?ml/min/100?ml; BF, 48.67?±?28.87?ml/min/100?ml; PI, 21?%?±?11?%. BF is significantly larger than PF, P?r?=?0.671, P?=?0.012).

Conclusion

The dual-input CT perfusion analysis method can be applied successfully to lung tumours. Initial results demonstrate a dual blood supply in primary lung cancer, in which the systemic circulation is dominant, and that the proportion of the two circulation systems is moderately dependent on tumour size.

Key Points

• A new CT perfusion technique can assess lung cancer's dual blood supply.
• A dual blood supply was confirmed with dominant bronchial circulation in lung cancer.
• The proportion of the two circulations is moderately dependent on tumour size.
• This new technique may benefit the management of lung cancer.

     

Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study

Objective:

To assess inter- and intrascanner variability in volumetry of solid pulmonary nodules in an anthropomorphic thoracic phantom using low-dose CT.

Methods:

Five spherical solid artificial nodules [diameters 3, 5, 8, 10 and 12 mm; CT density +100 Hounsfield units (HU)] were randomly placed inside an anthropomorphic thoracic phantom in different combinations. The phantom was examined on two 64-row multidetector CT (64-MDCT) systems (CT-A and CT-B) from different vendors with a low-dose protocol. Each CT examination was performed three times. The CT examinations were evaluated twice by independent blinded observers. Nodule volume was semi-automatically measured by dedicated software. Interscanner variability was evaluated by Bland–Altman analysis and expressed as 95% confidence interval (CI) of relative differences. Intrascanner variability was expressed as 95% CI of relative variation from the mean.

Results:

No significant difference in CT-derived volume was found between CT-A and CT-B, except for the 3-mm nodules (p<0.05). The 95% CI of interscanner variability was within ±41.6%, ±18.2% and ±4.9% for 3, 5 and ≥8 mm nodules, respectively. The 95% CI of intrascanner variability was within ±28.6%, ±13.4% and ±2.6% for 3, 5 and ≥8 mm nodules, respectively.

Conclusion:

Different 64-MDCT scanners in low-dose settings yield good agreement in volumetry of artificial pulmonary nodules between 5 mm and 12 mm in diameter. Inter- and intrascanner variability decreases at a larger nodule size to a maximum of 4.9% for ≥8 mm nodules.

Advances in knowledge:

The commonly accepted cut-off of 25% to determine nodule growth has the potential to be reduced for ≥8 mm nodules. This offers the possibility of reducing the interval for repeated CT scans in lung cancer screenings.Lung cancer is the primary cancer in males and the second most common cancer in females worldwide, causing 18% of the total number of deaths [1]. Many lung cancers are found at a relatively late stage, resulting in a 5-year survival of only 15% or less [2]. Low-dose CT is a promising screening method for early detection of lung cancer [3–7]. The first result indicates that CT lung cancer screening can reduce lung cancer-specific mortality [8].In lung cancer screening, treatment decisions usually depend on pulmonary nodule size for the nodules at first detection and on the growth rate at follow-up [4]. Therefore, it is essential to assess the nodule size and growth rate accurately and reproducibly [9,10]. Variability has been found in CT-derived nodule size assessment [11,12]. In view of the current practice of patients frequently undergoing follow-up examinations, sometimes not on the same scanner, reliable inter- and intrascanner reproducibility of nodule volumetry is important.However, previous studies reported inconsistent results regarding the reproducibility of nodule volumetry. Some in vitro studies have been performed in which artificial nodules were placed at known locations in a thoracic phantom without pulmonary vessels [13–15]. Some of these studies were based on older generation CT scanners [13,16]. These studies generally showed a small margin of variability in nodule volumetry for software from different vendors. On the other hand, in vivo studies have shown that variability can be considerable, with variability up to 25% for 15 to 500 mm³ nodules [11,17–19]. A study to investigate inter- and intrascanner variability under optimally controlled conditions, yet resembling human lungs, using a more realistic phantom, has not been performed. Nowadays, 64-row multidetector CT (64-MDCT) scanners are most commonly utilised, as well as in lung cancer screenings. The variability of nodule volumetry of these scanners impacts nodule management, e.g. the interval of repeated CT scanning. As an extension to our recent study on observer detection and accuracy of manual and semi-automated volumetry [10], the focus of this study is on reproducibility between and within 64-MDCT systems. We assessed the inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-MDCT, using randomly placed solid nodules in an anthropomorphic thoracic phantom with a background of pulmonary vasculature.